SME AI Governance Specialist
Leidos3025 Gaithersburg MDPosted 10 March 2026
Tech Stack
Job Description
This Department of War enterprise data and analytics program delivers mission-critical capabilities that enable leaders across the Department to make faster, better-informed decisions using trusted data at scale. Leidos Digital Modernization sector is seeking an experienced SME AI Governance Specialist to support the delivery, enhancement, and adoption of enterprise data and analytics products used across multiple DoD organizations.
In this role, you will work alongside government partners, engineers, and other industry teammates to translate operational and strategic requirements into scalable, production-ready solutions. You will contribute directly to product planning, execution, and continuous improvement—helping ensure capabilities are delivered efficiently, aligned to mission priorities, and positioned for sustained success.
This position offers the opportunity to work on a high-visibility, enterprise program at the intersection of data, analytics, and emerging AI technologies. Ideal candidates are motivated by mission impact, comfortable operating in complex stakeholder environments, and interested in building deep domain expertise while delivering capabilities with real-world national security outcomes.
Primary Responsibilities:
Develop and maintain AI governance frameworks ensuring compliance with ethical, legal, and organizational standards.
Conduct risk assessments to identify potential harms, biases, or compliance gaps in AI models and workflows.
Collaborate with engineering, legal, and mission teams to ensure AI solutions align with governance policies.
Prepare, maintain, and execute a System Engineering Plan (SEP) for managing all systems architecture and system engineering aspects.
Design, prepare, and document systems engineering and cybersecurity artifacts for the System.
Conduct systems engineering activities to specify, build, and maintain system engineering designs.
Support the Government in recommending and conducting enterprise system architecture activities.
Define, document, maintain, and promulgate APIs and technical standards for the System.
Design, engineer, integrate, and continuously improve the underlying infrastructure of the System.
Identify, prepare, track, secure, and integrate government, commercial, and open-source tools and services into the System.
Design, architect, engineer, and continuously improve the user interface (UI) and user experience (UX) components.
Build and maintain services and products to make production-ready AI/ML models accessible for customer use.
Design, architect, engineer, and continuously improve all aspects of cybersecurity elements of the System.
Perform site reliability engineering to build and maintain a reliable, scalable, and efficient System.
Participate in the Engineering Control Board (ECB) process for supporting all major engineering milestones and decisions.
Basic Qualifications:
Active Top Secret (TS) clearance with SCI eligibility.
Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Information Systems, or related technical discipline and 12–15 years of relevant experience OR Master’s degree in a related field and 10–13 years of relevant experience.
Minimum of 8 years of experience in systems engineering, AI governance, data governance, or a related field.
Strong understanding of ethical, legal, and organizational standards for AI systems.
Experience implementing AI/ML governance or responsible AI frameworks in enterprise environments.
Experience evaluating AI/ML models for performance, bias, explainability, and risk.
Experience integrating governance controls into AI/ML DevSecOps pipelines.
Experience supporting AI systems in cloud-native environments (AWS, Azure, or GCP).
Proficiency in systems engineering and cybersecurity practices.
Experience with enterprise system architecture activities.
Ability to define and maintain APIs and technical standards.
Experience with cloud environm ... (truncated, view full listing at source)
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